1. Field of the Invention
The invention relates to a magnetic resonance (MR) technique, more particularly to a q-space sampling method and a diffusion spectrum imaging method employing the sampling method.
2. Description of the Related Art
Diffusion spectrum imaging (hereinafter referred to as DSI) is an extended application of magnetic resonance (MR) techniques, and can be used to obtain information of tissue fibers non-invasively.
Conventional DSI techniques mainly include the following steps:
(a) First-stage sampling: Using a series of RF pulses and magnetic gradients, the spatial information of tissue can be distinguished via this spatial encoding procedure. This stage of sampling is considered as structural-image sampling;
(b) Second-stage sampling: In addition to spatial encoding, diffusion-weighted magnetic gradient (diffusion gradient for short) is applied. Because this step may add the information of water molecular motion to the imaged tissue, the applied diffusion gradients are considered as diffusion encodings. With these two stages of encodings, a structural image may be enhanced by diffusion-weighted contrast, and this kind of image is called diffusion weighted image (DWI). With different diffusion gradients, the contrasts of DWIs differ. Such is referred to as q-space sampling; and
(c) Signal processing: Since different directions and intensities of the diffusion gradients stand for different coordinates in a three-dimensional q-space, different DWIs with corresponding spatial position are arranged in one q-space according to originally designed q-space positions. After arranging these DWIs into q-space, inverse Fourier transform is applied to the q-space sampling data so as to reconstruct a probability density function (PDF) of water molecular motion, and orientation distribution functions of PDF are calculated using radial integrations. Information of the tissue fibers can be obtained by analyzing these orientation distribution functions.
One setback of DSI techniques is the low speed of sampling. According to a paper entitled “Using Track Similarity to Determine Optimum Sequence Parameters for Diffusion Spectrum Imaging” by L-W. Kuo et al. in Proceedings of the 13th Annual Meeting of ISMRM, Miami Beach, Fla., USA, 2005, the optimum parameter for DSI clinically is a setting of 515 diffusion-encoding gradients, and the maximum value of radius b of the sampled range of q-space is set as bmax=6000 s/mm2. However, under such optimum parameter settings, it takes more than an hour to obtain the sampled data in q-space. Long acquisition time is very disadvantageous in clinical applications.
There are two conventional ways of improving DSI sampling speed. One approach is to improve the sampling speed at the first stage, i.e., carrying out the first stage in image space. The other approach is to improve the sampling speed at the second stage, i.e., carrying out the second stage in q-space.
For conventional schemes to improve the sampling speed at the first stage in image space, reference can be made to the article entitled “k-space undersampling in PROPELLER imaging” by K. Arfanakis et al. in Magnetic Resonance in Medicine, vol. 53, (3), pp. 675-83, March, 2005. The scheme proposed in that article is mainly the use of k-space undersampling in PROPELLER MRI, and can reduce about 50% of sampling time when sampling DWIs. However, co-registration is additionally required in this conventional scheme.
For conventional schemes to improve the sampling speed at the first stage in image space, reference can be made to the article entitled “Simultaneous echo refocusing in EPI” by D.A. Feinberg et al. in Magnetic Resonance in Medicine, vol. 48, (1), pp. 1-5, 2002 and the paper entitled “Halving imaging time of whole brain diffusion spectrum imaging (DSI) using simultaneous echo refocusing (SER) EPI” by T. G. Reese et al. in Proceedings of the 14th Annual Meeting of ISMRM, Seattle, Wash., 2006. The methods proposed in these papers employ simultaneous echo refocusing (SER) so that two or more DWIs can be obtained in one echo train, thereby reducing data acquisition time. However, the SER method will reduce the quality of DWIs.
Another conventional scheme of improving the sampling speed at the first stage in image space is described in “Optimal Regular Volume Sampling” by T. Theussl in Proceedings of the IEEE visualization Conference, San Diego, Calif., USA, pp. 91-98, 2001. This paper points out that, in image space, use of body-center cubic sampling lattice or face-center cubic sampling lattice to sample computer tomography (CT) images or magnetic resonance images (MRI) can better prevent aliasing of structural images than rectangular sampling lattice (also known as Cartesian sampling lattice), and, therefore, similar image quality can be obtained using a smaller sampling number, so that sampling efficiency is enhanced. The rectangular sampling lattice, the body-center cubic sampling lattice and the face-center sampling lattice, as well as the respective generating matrices thereof are shown in FIG. 1.
However, the abovementioned conventional schemes are carried out in a structural image space, and are intended to improve the sampling speed at the first stage of DSI technique. They do not provide any improvement with regard to the speed of sampling in q-space at the second stage. Moreover, it is noted that, under current fast imaging techniques, sampling of structural images at the first stage takes up only a small portion of the time for the DSI sampling process. Therefore, the DSI sampling speed depends heavily on the sampling speed at the second stage. Thus, the three conventional schemes mentioned above still cannot effectively improve the DSI sampling speed.
However, the time required for generating contrast in DWIs by means of diffusion gradient magnetic field is constrained by the diffusion speed of water molecules physically, so that the speed of q-space sampling at the second stage is not easy to increase. A conventional method used to improve the speed of q-space sampling at the second stage is to reduce the sampling number in q-space in a fixed q-space sampling range (See “Using Track Similarity to Determine Optimum Sequence Parameters for Diffusion Spectrum Imaging” by L-W. Kuo et al. in Proceedings of the 13th Annual Meeting of ISMRM, Miami Beach, Fla., USA, 2005). Yet, the conventional method of q-space sampling is generally based on rectangular sampling lattice, and does not optimize the sampling lattice, so that erroneous identification of signals easily occurs as a result of aliasing. The increase in sampling speed is thus limited.